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In this article

• What is an API?
• 22 APIs every data scientist should learn
• How do you lot learn APIs?

APIs are the essential building blocks for data science. They provide primal data sources and enable data integration and visualization. In this web log, we look at the almost important APIs and how to leverage them.

From the "Pay with Paypal" or "Login with Facebook" buttons to games like Pokemon Go and travel aggregators such as Expedia, TripAdvisor, and Booking.com that allow you lot compare prices of flights and hotels, APIs are all around us. They help connect our world and carry valuable information from one website or application to another.

But how exercise APIs apply to data science and which APIs should exist part of your data science toolkit? Let's first by defining what an API is.

What is an API?

An Application Programming Interface (API) allows pieces of code to collaborate with i another. Developers use APIs to build their websites with specific features, like a Google Maps interface, instead of having to write lawmaking from scratch. Some may exist open-source, while others charge a fee for implementation. You typically demand to register a developer account or take another means of authentication for APIs.

An API typically has iii core elements:

• Access: Who is the user accessing the service?
• Asking: What is the service or data being requested? This includes both methods (what questions practise y'all need answered with the data or service solicited?) and parameters (supplementary details).
• Response: How does the system answer to the request?

Representational State Transfer (REST) provides a method for communication over web services, with commands like Go, PUT, Post, and DELETE.

APIs in R unremarkably use the HTTR package, while Python users volition want to become familiar with the Requests HTTP library. APIs role similar spider web applications only ship data-exchange outputs in formats like JSON, XML, etc., instead of HTML.

Here are some tutorials for a deep-dive into APIs for data science: CareerCon, DataQuest, and Towards Data Science.

I way to recall about an API is every bit a structured manner for you lot to obtain a permitted set of data from an application owner.

A detail API allows you lot to build on top of the rich datasets large, well-resourced organizations are building, either building live interactive web applications (for case, an app that uses the Spotify API to try to determine what instruments they might like from their liked songs on the Spotify app) or, as for near data scientists, using the information generated to build interesting analyses or models.

22 APIs every data scientist should learn

APIs can exist useful for many parts of the information science process, but have particular applications for machine learning. Many large tech companies and machine learning specialized startups provide ready-to-use frameworks for assay.

Here are some of the near popular APIs in information science:

• Amazon Motorcar Learning API

Congenital on the AWS cloud platform with a user-friendly interface, Amazon helps with prediction models, generates useful visualizations, and facilitates statistical analysis.

Amazon Machine Learning API is great for customer sensation. You can predict customer conversion, purchasing habits, and lifetime value, based on blazon and number of orders. Amazon'south API can also recognize human activity through sensor data and detect fraudulent users from analyzing web history.

Documentation: Amazon Machine Learning Documentation

Tutorial: AWS Machine Learning Samples. Examples of how y'all can utilize the Amazon Machine Learning API to build uncomplicated applications.

• IBM Watson Discovery API

IBM Watson allows you to sift through online search content and find patterns in enterprise data. It is all near applying cerebral skills to machines and studying how humans interact with applications.

This API makes it easier to translate text into language (speech to text and text to oral communication), determine how a message resonated with a detail audition, model users based on specific social characteristics, and answer frequently asked questions in real-time.

Documentation: IBM Cloud API

Tutorial: Create and query a data collection in IBM Watson Discovery, an official post that goes through to the timeline and process of running and getting actionable insights into IBM Watson.

• Google API

Google Maps is an important tool for whatever mapping program and for computing the distance between locations. Google Maps contains 17 unlike APIs nether Maps, Places, and Routes and has go 1 of the most pop spider web awarding evolution APIs, serving over ane million websites and apps and one billion users.

Documentation: Google Cloud APIs

Tutorial: Google has a bunch of API and tutorials all compiled into one place.

• Twilio API

The Twilio API allows you to transfer your programmatic skills to applications that accept to do with texts and calls. Create apps that can text your users or use their phones to communicate critical information. Manage and generate phone numbers programmatically through the Twilio API. Yous can also tap into WhatsApp programmatically too every bit verify phone number buying to reduce account signup fraud.

Documentation: Twilio Docs

Tutorial: How to build a chatbot, an example of how to use the Twilio console to build something from terminate-to-end with a mode to then integrate it into SMS or Whatsapp programmatically.

• Census.gov API

If you've e'er felt that you lot've needed disquisitional demographic and economic data from the U.S. government, this API helps y'all query that data and put together interesting applications and data projects congenital on one of the most reputable data collection agencies. You lot can aggregate historical information tied to a FIPS code that defines a certain Demography geographic area.

Documentation: Census Data API User Guide

Tutorial: A Tutorial for the Census Data API is a curt blog post that goes into how to get started with registering for an API key so making some sample queries. Y'all can use this website to figure out and go familiar with what data the demography contains.

• Spotify API

Get the metadata associated with the nigh popular songs (or even the near obscure). You'll besides get access to user information such as the songs related to the ones they like if yous become potency from them, allowing yous to build rich applications driven by the amass collection of music Spotify hosts likewise as the individual-level data it holds.

The API has a rate limit placed upon information technology and will return a status code 429 if over-used—other than that, you're free to explore once you've set up your Spotify developer account.

Documentation: Spotify Web API Documentation

Tutorial: Getting Started with Spotify's API is a Medium article that contains all of the steps you demand to go started with the Spider web API as well as Spotify, a Python library and API wrapper that can be used to quickly admission Spotify data.

• Yummly API

This API feeds in data about different recipes and the foods that compose it. Use information technology to come up up with new recipes and to analyze a current one. The API returns back JSON information, and supports both HTTP and HTTPS requests. You need to register for a developer business relationship in order to get access, and at that place is charge per unit limiting applied.

Documentation: Yummly API Documentation

Tutorial: Correct Yummly API call for a recipe – Stack Overflow is a Stack Overflow question that deals with how to properly structure a query for the Yummly API.

• New York Times API

Searching through the New York Times has never been easier with this API, which programmatically goes through different sections and articles all the way back to 1851. You lot can observe articles through a query filter or facet.

The API returns a max of 10 results at a time, while the meta node allows you lot to paginate through your results up to one,000. In exercise, it's meant for fine tooth-combing of a pick of articles for a detail time and a item discipline: you might be interested, for example, in what the New York Times wrote most a particular historical figure old between a certain date range.

The API not but offers New York Times results only also has Reuters and Associated Press articles likewise, which y'all tin can easily facet and search through.

Documentation: New York Times API Documentation

Tutorial: Scraping New York Times Articles with Python is a tutorial past UC Berkeley that shows the nuts of constructing a query around the API. In this case, they get through and wait for every Amnesty International mention between 1980 and 2004.

• Reddit API

Reddit is one of the earth'south largest social networks, which gives you an piece of cake pulse on what the Internet is thinking. Dubbed the "front page of the Internet", you can utilize the API to programmatically manage your Reddit account and to become data about which posts and subreddits are trending. You can even get so far every bit to automatically give Reddit golden to a list of different usernames.

The API is built to be able to allow for a broad scope of read and write applications, as well every bit to build datasets. Reddit is one of the earth's largest repositories of text data and sentiment analysis (in the form of upvotes and downvotes on content and comments). This property leads information technology to be an immensely valuable trove of data — this has led to many language generation motorcar learning models being trained on Reddit information.

Documentation: Reddit API Documentation

Tutorial: PRAW Repository PRAW stands for Python Reddit API Wrapper. The quickstart tutorial gets yous started on how to chop-chop work with Reddit's API for a variety of meaningful use cases.

• Zillow API

If you're looking for data on housing prices based on a variety of factors or a variety of online housing data, look no farther than the collection of APIs offered by Zillow. You'll exist able to stream real estate and mortgage data, allowing you to create websites that simulate real estate portals or do data assay on real estate patterns.

Documentation: Zillow API Documentation

Tutorial: Zillow API to Google Sheets is an article with a 3rd-party service (Apipheny) that makes it like shooting fish in a barrel to import Zillow data quickly into Google Sheets.

• Instagram API

Utilise the Instagram API to query metadata and data about Instagram posts and users. You'll be able to get posts around unlike hashtags, information virtually users and their following and follower counts, and much more than. Y'all'll need to sign upward to be approved every bit a developer but once yous are, you'll exist able to have access to a wealth of information and possibly the largest epitome repository in the world.

The legacy API is at present deprecated and has been divide into Basic Brandish API and Graph API.Utilise it to look at the social network and the profiles of different Instagram users and how they're related to one another.

Documentation: Instagram Programmer API Documentation

Tutorial: How To Navigate And Connect To Instagram's API

• Weather.gov API

The Weather.gov API is built past the National Atmospheric condition Service in the United states. Information technology allows you to get access to forecasts and dissimilar weather apps alive from an authoritative government source.

Documentation: Conditions.gov API Documentation

Tutorial: The Github repository contains lots of code and customs give-and-take for the The states National Weather Service API.

• Imgflip API

Ever wanted to tap into a stream of different memes? The Imgflip API allows you to practise only that. With a uncomplicated query, you can return a JSON object that contains 100 or so memes ordered by how many times they were captioned in the concluding 30 days—an interesting feature that lets yous become the virtually popular and trending memes.

You lot can then also generate memes programmatically with Imgflip's caption_image role. Images created with the API will be publicly attainable to everyone with the returned URL.

Documentation: Imgflip API Documentation

Tutorial: React.js Meme Generator Tutorial is a handy Youtube video that shows how you can integrate the Imgflip API with React.js to create an interactive web application dedicated to spawning memes.

• The SportsDB API

The SportsDB API compiles salaries and different salary caps across different teams in different sports. It will always remain free, only you can sign upwardly on Patreon for boosted features such as live scores.

You'll get JSON results back from players, teams and leagues around the world. For example, this is the profile for Mario Balotelli, a famous Italian striker. Yous'll be able to get positional data for players, detailed information most them, too every bit their wage and height.

The SportsDB API is the perfect plug-and-play API if you lot want alive sports scores and detailed player and league information.

Documentation: SportsDB API Documentation

Tutorial: The SportsDB forum has a department for third-political party projects congenital on acme of SportsDB.

• Crunchbase API

The Crunchbase API will help you get access to the exciting world of startups. Since individual financings scarcely have as much data transparency as public companies, Crunchbase represents the almost definitive database of startups, their funding rounds, and who provided the funding. Use their API to get a pulse on the latest financing rounds—what industries are getting them, who the funders are, and what companies are securing the financing they need to power forward.

Access to the full API requires an Enterprise or Applications License with CrunchBase, but you tin be authorized nether the Open Data Map programme to join data from people and system-level datasets to your own—y'all just need to be careful with attribution. The API is strictly read-only and is meant to take the incredible amount of data Crunchbase holds and put it towards applications and analyses that advance the startup ecosystem.

Documentation: Crunchbase API Documentation

Tutorial: How To Build An Automated Sales Pipeline With The Crunchbase API (Python)

• SkyWatch API

SkyWatch connects developers with satellite images around the globe, assuasive you lot to access to do interesting projects on images of Earth from space. They're partnered with NASA and dissimilar satellite providers and then you tin create datasets of maps and other views.

Documentation: SkyWatch API Documentation

Tutorial: How an Artificial Intelligence company uses satellite data is a example study congenital by the company behind SkyWatch.

• USGS Earthquakes API

Get real-time access to convulsion information as it comes in and is recorded around the world. Your application or information project volition soon exist able to ingest the pattern of the Earth's movement across decades. The API returns results in JSON, including the geographic location of earthquakes, and their depth and magnitude as well every bit other associated facts. It too returns which regions are currently under high alert for earthquakes.

Documentation: USGS Earthquake API Documentation

Tutorial: Earthquake Data API is a elementary tutorial that shows how with Python's requests library (or any other http library), you can construct an open, unauthenticated query — and get back information on where earthquakes occurred, their magnitude, and whether or not they caused a tsunami.

You might utilise this data to and then generate a predictive model for earthquakes and whether they will crusade tsunamis in their wake if you have more context on the geographic location.

• Johns Hopkins COVID-19 Data

This API uses the Johns Hopkins public data on COVID-19 incidence, and divides information technology past different regions and different reports, updating all of the fourth dimension.

Documentation: The documentation for the API can be plant hither.

Tutorial: This article sums upward different COVID-19 APIs.

• Facebook Graph API

Social media platforms have become integral to every consumer-focused business concern model. These APIs allow you lot to capture large information from posts, comments, and likes, which can be valuable for marketing and sales decisions. This aggregated information can facilitate opinion mining and sentiment analysis. Facebook's API allows yous access to Facebook information.

Documentation: Different Facebook documentation documents be for various products and APIs.

Tutorial: How to use Facebook Graph API and extract data using Python is a medium commodity on Towards Data Science that runs through how to employ the Graph API to become lists of people who are attending an event and the admins of said effect.

• Twitter API

The Twitter API allows yous to admission information most the world of tweets and allows you automatic access to read and write data. You tin create Tweets and Straight Messages automatically from it, though for information science purposes, the amount of data available can help with sentiment analysis and annihilation that requires a lot of text data around emerging or trending topics.

Documentation: Twitter API documentation

Tutorial: This folio provides live utilize cases for the Twitter API and tutorials on how to build those utilize cases.

• BigML

For supervised and unsupervised automobile learning, BigML is a RESTful API that enables real-time machine learning predictions using datasets, models, clusters, and anomaly detectors. Users tin can create a data source and then answer questions, like how many rooms volition be used in buildings architected by a construction company and which client service bug shoppers at retailers are most likely to encounter, and even forecast which TED talks will attract the highest viewership.

Documentation: BigML Documentation

Tutorial: The BigML Quick Outset guide helps y'all become set up with a series of elementary steps.

• Data Scientific discipline Toolkit

Pete Warden, founder of the OpenHeatMap project and writer of the Data Source Handbook for O'Reilly, too has a collection of open up information sets and open-source tools for data scientific discipline on Github every bit role of his Information Scientific discipline Toolkit API.

This API is based on a Linux distribution and comprises a REST/JSON API with command line, Python, and Javascript interfaces. Information technology allows you lot to extract of import insights, like geocodes, and execute information manipulations, like turning IP or street addresses to coordinates (breadth and longitude), files to text, HTML to text, text to dates/times, etc. To learn the R interface to use the toolkit, RDSTK is a helpful parcel for beginners.

Documentation: The Data Science Developer Docs are supposed to be here, but you lot might want to refer to the repository which has uptime as of writing.

Tutorial: The Data Scientific discipline Toolkit repository has different documentation and examples.

How do you lot learn APIs?

As a information scientist, you lot may be required to build your ain APIs that others tin access, so you volition need to recollect through unlike utilize cases. A common starting point is to exercise adding a web API through Flask, a micro Python interface.

In lodge to build your data science toolkit and acquire APIs, yous will desire to know querying languages like SQL; the Python programming language and libraries similar scipy, TensorFlow, scikit, pandas, numpy, and matplotlib; frameworks like Spark and Scala; and tools for data visualization, regression, and high-performance data analysis.

Equally y'all master data science through programs like Springboard'south information science bootcamp, you can find countless online resources to do with APIs, such equally:

• RapidAPI, the nigh extensive online API marketplace featuring 7500 APIs
• ProgrammableWeb, which has a huge searchable database of API tutorials and industry news and inquiry
• Courses like FreeCodeCamp's "APIs for Beginners" free video tutorial series, which covers popular web APIs, like the Twitter and Spotify APIs

In one case you understand APIs, you can perform all kinds of interesting tasks, from stock prediction to facial recognition and customer feedback synthesis.

By contributing to more than open-source APIs, data scientists can expand our capacity to process large information by increasing data volume, giving faster admission to data storage centers, and quickly developing new products and services through cerebral APIs, which can transform inputs into data formats readable by other systems through machine learning.

To fast-rail your noesis of APIs and preparation for a data science career, check out Springboard's data scientific discipline, data engineer, and machine learning bootcamps.

Is data science the correct career for yous?

Springboard offers a comprehensive data science bootcamp. You'll work with a 1-on-one mentor to learn almost data scientific discipline, information wrangling, machine learning, and Python—and finish it all off with a portfolio-worthy capstone project.

Check out Springboard's Data Science Career Track to see if you qualify.

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Source: https://www.springboard.com/blog/data-science/top-apis-for-data-scientists/

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